Systems and methods for using artificial intellegence for compliance regulation

Abstract

A method for using artificial intelligence for compliance regulation includes capturing one or more document files from one or more websites according to a list of trusted websites. The method may further include extracting a plurality of document data from the one or more document files. The method may further include providing the plurality of document data to a comparison machine-learning model. The comparison machine-learning model may be trained to identify changes within the plurality of document data and a plurality of previous document data and generate a report based on the identified changes. The method may further include transmitting the report to a user interface.

What is claimed is: 
     
         1 . A computer-implemented method for using artificial intelligence for compliance regulation, the method comprising:
 capturing, by one or more processors, one or more document files from one or more websites according to a list of trusted websites;   extracting, by the one or more processors, a plurality of document data from the one or more document files;   providing, by the one or more processors, the plurality of document data to a comparison machine-learning model trained to identify changes within the plurality of document data and a plurality of previous document data and generate a report based on the identified changes; and   transmitting the report to a user interface by the one or more processors.   
     
     
         2 . The computer-implemented method of  claim 1 , wherein the capturing is according to a predetermined schedule. 
     
     
         3 . The computer-implemented method of  claim 1 , wherein the comparison machine-learning model is an artificial intelligence model. 
     
     
         4 . The computer-implemented method of  claim 3 , wherein the plurality of document data is provided to the comparison machine-learning model as fragmented document data. 
     
     
         5 . The computer-implemented method of  claim 4 , wherein the fragmented document data is fragmented into one or more chunks of document data, each of a predetermined size. 
     
     
         6 . The computer-implemented method of  claim 1 , wherein the report generated by the comparison machine-learning model is in a natural language format. 
     
     
         7 . The computer-implemented method of  claim 1 , further comprising:
 providing, by the one or more processors, the report to a chat artificial intelligence model trained to process one or more user questions and generate one or more responses;   transmitting the one or more user questions to the user interface by the one or more processors.   
     
     
         8 . A system for using artificial intelligence for compliance regulation, the system comprising:
 a memory storing instructions and a comparison machine-learning model trained to identify changes within a plurality of document data and a plurality of previous document data and generate a report based on the identified changes; and   a processor operatively connected to the memory and configured to execute the instructions to perform operations including:
 capturing, by the processor, one or more document files from one or more websites according to a list of trusted websites; 
 extracting, by the processor, the plurality of document data from the one or more document files; 
 providing, by the processor, the plurality of document data to the comparison machine-learning model; and 
 transmitting the report to a user interface by the one or more processors. 
   
     
     
         9 . The system of  claim 8 , wherein the capturing is according to a predetermined schedule. 
     
     
         10 . The system of  claim 8 , wherein the comparison machine-learning model is an artificial intelligence model. 
     
     
         11 . The system of  claim 10 , wherein the plurality of document data is provided to the comparison machine-learning model as fragmented document data. 
     
     
         12 . The system of  claim 11 , wherein the fragmented document data is fragmented into one or more chunks of document data, each of a predetermined size. 
     
     
         13 . The system of  claim 8 , wherein the report generated by the comparison machine-learning model is in a natural language format. 
     
     
         14 . The system of  claim 8 , further comprising:
 providing, by the processor, the report to a chat artificial intelligence model trained to process one or more user questions and generate one or more responses;   transmitting the one or more user questions to the user interface by the processor.   
     
     
         15 . A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, perform operations including:
 capturing, by one or more processors, one or more document files from one or more websites according to a list of trusted websites;   extracting, by the one or more processors, a plurality of document data from the one or more document files;   providing, by the one or more processors, the plurality of document data to a comparison machine-learning model trained to identify changes within the plurality of document data and a plurality of previous document data and generate a report based on the identified changes; and   transmitting the report to a user interface by the one or more processors.   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the capturing is according to a predetermined schedule. 
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , wherein the plurality of document data is provided to the comparison machine-learning model as fragmented document data. 
     
     
         18 . The non-transitory computer-readable medium of  claim 17 , wherein the fragmented document data is fragmented into one or more chunks of document data, each of a predetermined size. 
     
     
         19 . The non-transitory computer-readable medium of  claim 17 , wherein the report generated by the comparison machine-learning model is in a natural language format. 
     
     
         20 . The non-transitory computer-readable medium of  claim 17 , further comprising:
 providing, by the one or more processors, the report to a chat artificial intelligence model trained to process one or more user questions and generate one or more responses;   transmitting the one or more user questions to the user interface by the one or more processors.